Library BRVM

BRVM

Description

English

This R package provides a user-friendly interface for accessing data from the BRVM, which is a regional stock exchange serving multiple West African countries. With this package, users can easily retrieve historical stock price data, trading volumes, and other financial indicators for a variety of stocks traded on the BRVM.

The package is designed to simplify the process of gathering and analyzing financial data, making it easier for researchers, investors, and other users to extract insights and make informed decisions based on the information available. Overall, BRVM library is a valuable tool for anyone looking to gain a better understanding of the BRVM and the financial markets in West Africa.

Français

Ce package R fournit une interface conviviale pour accéder aux données de la BRVM, qui est une bourse régionale desservant plusieurs pays d’Afrique de l’Ouest. Avec ce package, les utilisateurs peuvent facilement récupérer des données historiques sur les prix des actions, les volumes de transactions et d’autres indicateurs financiers pour une variété d’actions négociées sur la BRVM.

Le package est conçu pour simplifier le processus de collecte et d’analyse de données financières, ce qui facilite la tâche des chercheurs, des investisseurs et d’autres utilisateurs pour extraire des informations et prendre des décisions éclairées en se basant sur les informations disponibles. Dans l’ensemble, notre package R est un outil précieux pour quiconque cherche à mieux comprendre la BRVM et les marchés financiers en Afrique de l’Ouest.

Installation guidelines

You can install the development version of BRVM from github with:

# github dev version
## We can use devtools
# install.packages("devtools")
devtools::install_github("Koffi-Fredysessie/BRVM")

# Or use remotes
# install.packages("remotes")
remotes::install_github("Koffi-Fredysessie/BRVM")

Html version of the Readme

Since the size of the readme is huge due to the charts, you can visit the html version of the readme on RPubs

library(BRVM)

The BRVM_ticker_desc() function

It receives no argument and returns BRVM tickers information such as its full name, sector and country.

# Display tickers of BRVM
tickers <- BRVM_ticker_desc()
tickers

Ticker	Company name	Sector	Country
ABJC	SERVAIR ABIDJAN COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
BICC	BICI COTE D’IVOIRE	FINANCE	IVORY COAST
BNBC	BERNABE COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
BOAB	BANK OF AFRICA BENIN	FINANCE	BENIN
BOABF	BANK OF AFRICA BURKINA FASO	FINANCE	BURKINA FASO
BOAC	BANK OF AFRICA COTE D’IVOIRE	FINANCE	IVORY COAST
BOAM	BANK OF AFRICA MALI	FINANCE	MALI
BOAN	BANK OF AFRICA NIGER	FINANCE	NIGER
BOAS	BANK OF AFRICA SENEGAL	FINANCE	SENEGAL
CABC	SICABLE COTE D’IVOIRE	INDUSTRY	IVORY COAST
CBIBF	CORIS BANK INTERNATIONAL BURKINA FASO	FINANCE	BURKINA FASO
CFAC	CFAO MOTORS COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
CIEC	CIE COTE D’IVOIRE	PUBLIC SERVICE	IVORY COAST
ECOC	ECOBANK COTE D’IVOIRE	FINANCE	IVORY COAST
ETIT	Ecobank Transnational Incorporated TOGO	FINANCE	TOGO
FTSC	FILTISAC COTE D’IVOIRE	INDUSTRY	IVORY COAST
NEIC	NEI-CEDA COTE D’IVOIRE	INDUSTRY	IVORY COAST
NSBC	NSIA BANQUE COTE D’IVOIRE	FINANCE	IVORY COAST
NTLC	NESTLE COTE D’IVOIRE	INDUSTRY	IVORY COAST
ONTBF	ONATEL BURKINA FASO	PUBLIC SERVICE	BURKINA FASO
ORAC	ORANGE COTE D’IVOIRE	PUBLIC SERVICE	IVORY COAST
ORGT	ORAGROUP TOGO	FINANCE	TOGO
PALC	PALM COTE D’IVOIRE	AGRICULTURE	IVORY COAST
PRSC	TRACTAFRIC MOTORS COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
SAFC	SAFCA COTE D’IVOIRE	FINANCE	IVORY COAST
SCRC	SUCRIVOIRE COTE D’IVOIRE	AGRICULTURE	IVORY COAST
SDCC	SODE COTE D’IVOIRE	PUBLIC SERVICE	IVORY COAST
SDSC	BOLLORE TRANSPORT & LOGISTICS COTE D’IVOIRE	TRANSPORT	IVORY COAST
SEMC	CROWN SIEM COTE D’IVOIRE	INDUSTRY	IVORY COAST
SGBC	SOCIETE GENERALE COTE D’IVOIRE	FINANCE	IVORY COAST
SHEC	VIVO ENERGY COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
SIBC	SOCIETE IVOIRIENNE DE BANQUE COTE D’IVOIRE	FINANCE	IVORY COAST
SICC	SICOR COTE D’IVOIRE	AGRICULTURE	IVORY COAST
SIVC	AIR LIQUIDE COTE D’IVOIRE	INDUSTRY	IVORY COAST
SLBC	SOLIBRA COTE D’IVOIRE	INDUSTRY	IVORY COAST
SMBC	SMB COTE D’IVOIRE	INDUSTRY	IVORY COAST
SNTS	SONATEL SENEGAL	PUBLIC SERVICE	SENEGAL
SOGC	SOGB COTE D’IVOIRE	AGRICULTURE	IVORY COAST
SPHC	SAPH COTE D’IVOIRE	AGRICULTURE	IVORY COAST
STAC	SETAO COTE D’IVOIRE	OTHER	IVORY COAST
STBC	SITAB COTE D’IVOIRE	INDUSTRY	IVORY COAST
SVOC	MOVIS COTE D’IVOIRE	TRANSPORT	IVORY COAST
TTLC	TOTAL COTE D’IVOIRE	DISTRIBUTION	IVORY COAST
TTLS	TOTAL SENEGAL	DISTRIBUTION	SENEGAL
TTRC	TRITURAF Ste en Liquid	INDUSTRY	IVORY COAST
UNLC	UNILEVER COTE D’IVOIRE	INDUSTRY	IVORY COAST
UNXC	UNIWAX COTE D’IVOIRE	INDUSTRY	IVORY COAST

The BRVM_index() function :

It receives no argument and returns a table of updated data (with as table header: indexes, previous closing, closing, change (%), Year to Date Change) on all the indices available on the BRVM exchange.

the_index <- BRVM_index() 
the_index

Indexes	Previous closing	Closing	Change (%)	Year to Date Change
BRVM-30	100.01	99.71	-0.30	0.00
BRVM - AGRICULTURE	285.50	281.76	-1.31	-0.66
BRVM - OTHER SECTOR	1295.58	1295.58	0.00	-7.32
BRVM - COMPOSITE	199.95	199.37	-0.29	0.85
BRVM - DISTRIBUTION	350.49	346.02	-1.28	0.69
BRVM - FINANCE	74.52	74.53	0.01	-0.66
BRVM - INDUSTRY	98.71	98.33	-0.38	0.92
BRVM - PRESTIGE	102.77	102.61	-0.16	0.00
BRVM - PRINCIPAL	94.97	94.56	-0.43	0.00
BRVM - PUBLIC SERVICES	482.03	480.97	-0.22	2.23
BRVM - TRANSPORT	350.06	345.28	-1.37	0.35

The BRVM_get(“.symbol”, “.from”, “.to”) function

This function will get the data of the companies listed on the BVRM stock exchange in Rich Bourse website. The function takes a single parameter, .symbol (which represents the “Ticker”). The function will automatically format tickers you enter in uppercase using toupper() and then ensure that the passed ticker is in a Google spreadsheet of allowed tickers.

• .symbol : A vector of symbols, like: c(“BICC”,“XOM”,“SlbC”) ;
• .from : A quoted start date, ie. “2020-01-01” or “2020/01/01”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD” ;
• .to : A quoted end date, ie. “2022-01-31” or “2022/01/31”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”.

#' Displaying data of SONATEL Senegal stock
BRVM_get(.symbol = "snts")
#> [1] "SNTS"
#> # A tibble: 251 × 6
#>    Date        Open  High   Low Close Volume
#>    <date>     <dbl> <dbl> <dbl> <dbl>  <dbl>
#>  1 2022-04-05 15775 15775 15660 15750  25792
#>  2 2022-04-06 15800 15895 15750 15800   7436
#>  3 2022-04-07 15800 15900 15750 15900   1265
#>  4 2022-04-08 15900 15995 15800 15900   1164
#>  5 2022-04-11 15895 15900 15800 15800   4252
#>  6 2022-04-12 15800 15800 15780 15800   6561
#>  7 2022-04-13 15800 15865 15795 15850   5409
#>  8 2022-04-14 15855 15900 15850 15900  16957
#>  9 2022-04-15 15995 15995 15900 15900    791
#> 10 2022-04-19 15900 15995 15895 15900  31217
#> # … with 241 more rows

symbols <- c("BiCc","XOM","SlbC")   # We use here three tickers
data_tbl <- BRVM_get(.symbol = symbols, .from = "2020-01-01", .to = Sys.Date() - 1)
#> [1] "BICC" "SLBC"

# Display the first twenty observations of the table
head(data_tbl, 20)
#> # A tibble: 20 × 7
#>    Date        Open  High   Low Close Volume Ticker
#>    <date>     <dbl> <dbl> <dbl> <dbl>  <dbl> <chr> 
#>  1 2020-01-10  6500  6500  6500  6500     24 BICC  
#>  2 2020-01-13  6370  6500  6370  6500     29 BICC  
#>  3 2020-01-14  6495  6495  6495  6495     10 BICC  
#>  4 2020-01-29  6010  6010  6010  6010     24 BICC  
#>  5 2020-01-30  6000  6000  6000  6000     50 BICC  
#>  6 2020-02-04  5800  5800  5800  5800     12 BICC  
#>  7 2020-02-07  5650  5650  5650  5650      5 BICC  
#>  8 2020-02-10  5500  5500  5500  5500      5 BICC  
#>  9 2020-02-14  5300  5300  5300  5300      9 BICC  
#> 10 2020-02-17  4910  4910  4910  4910    210 BICC  
#> 11 2020-02-18  4910  4910  4910  4910     50 BICC  
#> 12 2020-02-20  4895  4895  4895  4895      5 BICC  
#> 13 2020-02-21  4895  4895  4890  4890     13 BICC  
#> 14 2020-02-25  4525  4525  4525  4525     16 BICC  
#> 15 2020-02-26  4435  4435  4430  4430     21 BICC  
#> 16 2020-02-27  4345  4760  4335  4760   1809 BICC  
#> 17 2020-03-03  4745  4750  4745  4750     11 BICC  
#> 18 2020-03-05  4700  4700  4700  4700      5 BICC  
#> 19 2020-03-06  4695  4695  4695  4695      6 BICC  
#> 20 2020-03-11  4345  4450  4345  4450    135 BICC


# Display the last twenty elements of the table
tail(data_tbl, 20)
#> # A tibble: 20 × 7
#>    Date        Open  High   Low Close Volume Ticker
#>    <date>     <dbl> <dbl> <dbl> <dbl>  <dbl> <chr> 
#>  1 2023-02-14 79000 79000 79000 79000      2 SLBC  
#>  2 2023-02-15 80000 80000 79000 79000      2 SLBC  
#>  3 2023-02-17 78000 78000 78000 78000      5 SLBC  
#>  4 2023-02-21 80000 80000 80000 80000      5 SLBC  
#>  5 2023-02-23 80000 80000 80000 80000     18 SLBC  
#>  6 2023-02-24 80000 80000 80000 80000      6 SLBC  
#>  7 2023-02-27 80000 80000 80000 80000     98 SLBC  
#>  8 2023-02-28 80000 80000 80000 80000     11 SLBC  
#>  9 2023-03-02 80000 80000 80000 80000     11 SLBC  
#> 10 2023-03-08 80000 80000 80000 80000      2 SLBC  
#> 11 2023-03-09 80000 80000 80000 80000      2 SLBC  
#> 12 2023-03-13 80005 80005 80000 80000     12 SLBC  
#> 13 2023-03-14 80000 80000 80000 80000      1 SLBC  
#> 14 2023-03-20 80000 80000 80000 80000      3 SLBC  
#> 15 2023-03-21 80000 80000 80000 80000      4 SLBC  
#> 16 2023-03-27 78000 80000 78000 80000    169 SLBC  
#> 17 2023-03-28 80000 80000 80000 80000    435 SLBC  
#> 18 2023-03-30 80000 80000 80000 80000      3 SLBC  
#> 19 2023-03-31 80000 80000 80000 80000      1 SLBC  
#> 20 2023-04-04 80000 86000 80000 86000      3 SLBC

The BRVM_get1(“ticker”, “Period”, “from”, “to”) function

This function will get data of the companies listed on the BVRM stock exchange through the sikafinance site. The function takes in a single parameter of ticker and will auto-format the tickers you input into all upper case by using toupper()

• ticker : A vector of ticker, like: c(“BICC”,“XOM”,“SlbC”, “BRvm10”);
• Period : Numeric number indicating time period. Valid entries are 0, 1, 5, 30, 91, and 365 representing respectively ‘daily’, ‘one year’, ‘weekly’, ‘monthly’, ‘quarterly’ and ‘yearly’;
• from : A quoted start date, ie. “2020-01-01” or “2020/01/01”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”;
• to : A quoted end date, ie. “2022-01-31” or “2022/01/31”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”

** NB : There is a small difference between the BRVM_get and BRVM_get1 functions. * With BRVM_get it is only possible to download tickers’ daily data. * But with BRVM_get1, you can download daily, weekly, monthly, annual tickers’ data, indices and even market capitalization.

#' Displaying data of SONATEL Senegal stock
BRVM_get1("snts")
#> [1] "We obtained SNTS data from 2023-01-06 to 2023-04-05"
#> # A tibble: 64 × 5
#>    Date        Open  High   Low Close
#>    <date>     <int> <int> <int> <int>
#>  1 2023-01-06 15100 15100 15000 15000
#>  2 2023-01-09 14990 15000 14990 15000
#>  3 2023-01-10 14600 14800 14600 14800
#>  4 2023-01-11 15000 15000 14800 14800
#>  5 2023-01-12 14795 15000 14795 15000
#>  6 2023-01-13 14990 14990 14900 14900
#>  7 2023-01-16 14895 14900 14895 14900
#>  8 2023-01-17 14850 14850 14840 14840
#>  9 2023-01-18 14800 14900 14800 14900
#> 10 2023-01-19 14780 14800 14780 14800
#> # … with 54 more rows

# Get daily data of all indexes
all_ind <- BRVM_get1("ALL INDEXES", Period = 0, from = "2020-01-04", to = "2023-03-24") 
#> [1] "We obtained BRVM10 data from 2019-12-26 to 2023-01-04"
#> [1] "We obtained BRVMAG data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMC data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMAS data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMDI data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMFI data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMIN data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMSP data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMTR data from 2019-12-26 to 2023-03-24"
#> [1] "We obtained BRVMPR data from 2023-01-01 to 2023-03-24"
#> [1] "We obtained BRVMPA data from 2023-01-04 to 2023-03-24"
#> [1] "We obtained BRVM30 data from 2023-01-01 to 2023-03-24"
#> [1] "We obtained CAPIB data from 2020-01-02 to 2023-03-24"

# display the first two tens elements of the table
head(all_ind, 20)
#> # A tibble: 20 × 7
#>    Date        Open  High   Low Close Volume Ticker
#>    <date>     <dbl> <dbl> <dbl> <dbl>  <dbl> <chr> 
#>  1 2022-12-26  169.  169.  169.  169.      0 BRVM10
#>  2 2022-12-27  169.  169.  169.  169.      0 BRVM10
#>  3 2022-12-28  167.  167.  167.  167.      0 BRVM10
#>  4 2022-12-29  167.  167.  167.  167.      0 BRVM10
#>  5 2022-12-30  166.  166.  166.  166.      0 BRVM10
#>  6 2023-01-02  166.  166.  166.  166.      0 BRVM10
#>  7 2023-01-03  166.  166.  166.  166.      0 BRVM10
#>  8 2023-01-04  166.  166.  166.  166.      0 BRVM10
#>  9 2022-09-26  163.  163.  163.  163.      0 BRVM10
#> 10 2022-09-27  162.  162.  162.  162.      0 BRVM10
#> 11 2022-09-28  162.  162.  162.  162.      0 BRVM10
#> 12 2022-09-29  163.  163.  163.  163.      0 BRVM10
#> 13 2022-09-30  164.  164.  164.  164.      0 BRVM10
#> 14 2022-10-03  162.  162.  162.  162.      0 BRVM10
#> 15 2022-10-04  162.  162.  162.  162.      0 BRVM10
#> 16 2022-10-05  161.  161.  161.  161.      0 BRVM10
#> 17 2022-10-06  161.  161.  161.  161.      0 BRVM10
#> 18 2022-10-07  161.  161.  161.  161.      0 BRVM10
#> 19 2022-10-10  160.  160.  160.  160.      0 BRVM10
#> 20 2022-10-11  160.  160.  160.  160.      0 BRVM10

# display the two tens of the last elements of the table
tail(all_ind, 20)
#> # A tibble: 20 × 7
#>    Date          Open    High     Low   Close Volume Ticker
#>    <date>       <dbl>   <dbl>   <dbl>   <dbl>  <dbl> <chr> 
#>  1 2020-02-26 4281311 4281311 4281311 4281311      0 CAPIB 
#>  2 2020-02-27 4314933 4314933 4314933 4314933      0 CAPIB 
#>  3 2020-02-28 4346515 4346515 4346515 4346515      0 CAPIB 
#>  4 2020-03-02 4424073 4424073 4424073 4424073      0 CAPIB 
#>  5 2020-03-03 4379647 4379647 4379647 4379647      0 CAPIB 
#>  6 2020-03-04 4369550 4369550 4369550 4369550      0 CAPIB 
#>  7 2020-03-05 4342229 4342229 4342229 4342229      0 CAPIB 
#>  8 2020-03-06 4359879 4359879 4359879 4359879      0 CAPIB 
#>  9 2020-03-09 4338293 4338293 4338293 4338293      0 CAPIB 
#> 10 2020-03-10 4357221 4357221 4357221 4357221      0 CAPIB 
#> 11 2020-03-11 4332656 4332656 4332656 4332656      0 CAPIB 
#> 12 2020-03-12 4318096 4318096 4318096 4318096      0 CAPIB 
#> 13 2020-03-13 4318112 4318112 4318112 4318112      0 CAPIB 
#> 14 2020-03-16 4285184 4285184 4285184 4285184      0 CAPIB 
#> 15 2020-03-17 4301727 4301727 4301727 4301727      0 CAPIB 
#> 16 2020-03-18 4288582 4288582 4288582 4288582      0 CAPIB 
#> 17 2020-03-19 4207231 4207231 4207231 4207231      0 CAPIB 
#> 18 2020-03-20 4209788 4209788 4209788 4209788      0 CAPIB 
#> 19 2020-03-23 4154445 4154445 4154445 4154445      0 CAPIB 
#> 20 2020-03-24 4144325 4144325 4144325 4144325      0 CAPIB

# To get yearly data
yearly_data <- BRVM_get1(c("brvmtr", "BiCc", "BOAS"), Period = 365 ) 

# display the first two tens elements of the table
head(yearly_data, 20) 
#> # A tibble: 20 × 6
#>    Date         Open   High    Low  Close Ticker
#>    <date>      <dbl>  <dbl>  <dbl>  <dbl> <chr> 
#>  1 2003-04-11   74.0   88.6   73.6   88.6 BRVMTR
#>  2 2004-01-02   88.6   89.2   72.9   89.2 BRVMTR
#>  3 2005-01-03   89.2  107.    70.7  104.  BRVMTR
#>  4 2006-01-02  104.   158.   104.   153.  BRVMTR
#>  5 2007-01-02  153.   275.   149.   249.  BRVMTR
#>  6 2008-01-02  249.   386.   226.   296.  BRVMTR
#>  7 2009-01-02  275.   296.   227.   236.  BRVMTR
#>  8 2010-01-04  236.   259.   224.   238.  BRVMTR
#>  9 2011-01-03  238.   249.   204.   239   BRVMTR
#> 10 2012-01-02  239    349.   201.   349.  BRVMTR
#> 11 2013-01-02  349.   794.   339.   789.  BRVMTR
#> 12 2014-01-02  789.  1213.   601.  1213.  BRVMTR
#> 13 2015-01-02 1213.  1525.   653.  1525.  BRVMTR
#> 14 2016-01-04 1525.  1525.  1216.  1432.  BRVMTR
#> 15 2017-01-02 1432.  1433.   764.  1203.  BRVMTR
#> 16 2018-01-02 1114.  1193.   966.   966.  BRVMTR
#> 17 2019-06-03  403.   429.   311.   367.  BRVMTR
#> 18 2020-01-01  367.   475.   292.   379.  BRVMTR
#> 19 2021-01-04  376.   622.   325    622.  BRVMTR
#> 20 2022-01-03  667.   667.   295.   342.  BRVMTR

# display the two tens of the last elements of the table
tail(yearly_data, 20) 
#> # A tibble: 20 × 6
#>    Date        Open  High   Low Close Ticker
#>    <date>     <dbl> <dbl> <dbl> <dbl> <chr> 
#>  1 2014-01-02  5650  7848  5650  7800 BICC  
#>  2 2015-01-02  8385 10750  7800 10100 BICC  
#>  3 2016-01-04 10000 10700  8566  9890 BICC  
#>  4 2017-01-05  9750 10000  6440  8490 BICC  
#>  5 2018-01-02  8700  8750  3795  7900 BICC  
#>  6 2019-01-04  7550  7550  3710  6800 BICC  
#>  7 2020-01-01  6800  6890  2855  6680 BICC  
#>  8 2021-01-04  6680  7525  4280  7400 BICC  
#>  9 2022-01-03  7250  7250  5550  6850 BICC  
#> 10 2023-01-02  6500  6850  5785  6275 BICC  
#> 11 2014-12-10  1613  3225  1613  3225 BOAS  
#> 12 2015-01-02  3370  4300  2900  3950 BOAS  
#> 13 2016-01-04  3700  4101  2000  2350 BOAS  
#> 14 2017-01-02  2325  3875  2035  2500 BOAS  
#> 15 2018-01-02  2400  3250  1700  2020 BOAS  
#> 16 2019-01-02  1900  2000  1500  1545 BOAS  
#> 17 2020-01-01  1550  1700  1295  1495 BOAS  
#> 18 2021-01-04  1480  2750  1340  2350 BOAS  
#> 19 2022-01-03  2350  2780  2200  2450 BOAS  
#> 20 2023-01-02  2580  2585  2175  2175 BOAS

The BRVM.index() function :

It receives no argument and returns the name of all indexes available on BRVM Stock Exchange.

BRVM.index()
#>  [1] "BRVMAG" "BRVMC"  "BRVMAS" "BRVMDI" "BRVMFI" "BRVMIN" "BRVMSP" "BRVMTR"
#>  [9] "BRVMPR" "BRVMPA" "BRVM30"

The BRVM_bySector(“.sectors”) function :

This function will take in the name of sector(s) and returns data for companies belonging to that/those sector(s)

• .sectors : A vector of sectors you wish to have returned.

# Get informations about brvm sectors like other and agriculture sectors
BRVM_bySector(.sectors = c("Other", "Agriculture"))
#> [1] "There is 1 company that belongs to Other's sector"
#> # A tibble: 1 × 6
#>   Ticker Volume `Previous price`  Open Close `Change (%)`
#>   <chr>   <dbl>            <dbl> <dbl> <dbl>        <dbl>
#> 1 STAC      750             1050  1050  1050            0
#> [1] "There are 5 companies that belong to Agriculture's sector"
#> # A tibble: 5 × 6
#>   Ticker Volume `Previous price`  Open Close `Change (%)`
#>   <chr>   <dbl>            <dbl> <dbl> <dbl>        <dbl>
#> 1 PALC     3423            10945 10945 10945         0   
#> 2 SCRC     6262              680   710   680        -4.23
#> 3 SICC        0             5950     0  5950         0   
#> 4 SOGC       90             5580  5580  5580         0   
#> 5 SPHC      207             4805  5000  4800        -4
#> # A tibble: 6 × 8
#>   Ticker `Company name`           Volume Previous p…¹  Open Close Chang…² Sector
#>   <chr>  <chr>                     <dbl>        <dbl> <dbl> <dbl>   <dbl> <chr> 
#> 1 STAC   SETAO COTE D'IVOIRE         750         1050  1050  1050    0    Other 
#> 2 PALC   PALM COTE D'IVOIRE         3423        10945 10945 10945    0    Agric…
#> 3 SCRC   SUCRIVOIRE COTE D'IVOIRE   6262          680   710   680   -4.23 Agric…
#> 4 SICC   SICOR COTE D'IVOIRE           0         5950     0  5950    0    Agric…
#> 5 SOGC   SOGB COTE D'IVOIRE           90         5580  5580  5580    0    Agric…
#> 6 SPHC   SAPH COTE D'IVOIRE          207         4805  5000  4800   -4    Agric…
#> # … with abbreviated variable names ¹​`Previous price`, ²​`Change (%)`

The BRVM_stock_market(“.weekday”) function :

This function receives as input a day of the week (working day) and returns the official quotation revews of that day. * .weekday : A quoted date, ie. “2022-01-31” or “2022/01/31”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”. Must not be a weekend or a holiday.

# The BOC of 2022-02-23
BRVM_stock_market("2022-02-23")

Ticker	Equity	Volume	Value	Previous price	Open	Close	Change (%)	Annual change (%)	Reference price	Low	High	Net Income	Date	Compartment	Yield Net (%)	PER
INDUSTRY SECTOR				-4.85%			NA
CABC	SICABLE CI	517	665880	1225	1225	1225	0	20.69	1225	1000	1030	133.00	02/08/2021	1er	10.86	6.22
FTSC	FILTISAC CI	840	1343210	1560	1600	1600	-2.5	-7.14	1600	17020	19780	235.00	31/08/2021	1er	14.69	6.35
NEIC	NEI-CEDA CI	10866	8915565	880	875	850	-7.37	40.80	950	33	37	9.00	28/06/2021	1er	0.00	15.14
NTLC	NESTLE CI	207	1168515	5645	5640	5645	-0.09	22.58	5650	1850	2140	363.67	30/07/2021	2eme	6.44	5.97
SEMC	CROWN SIEM CI	602	445980	730	750	750	2.74	-1.96	730	12835	14915	14.40	28/12/2021	2eme	1.97	24.97
SIVC	AIR LIQUIDE CI	1549	1255650	925	900	860	-7.03	-3.91	925	3980	4620	63.00	29/09/2020	1er	0.00	0.00
SLBC	SOLIBRA CI			167700	160000	167700	4.81	7.50	160000	115625	134375	2736.00	03/08/2021	1er	1.71	15.03
SMBC	SMB CI	144	1069980	7495	7495	7495	4.83	8.62	7150	7770	9030	810.00	15/07/2021	1er	11.33	5.93
STBC	SITAB CI	111	961900	5800	5800	5800	0	-6.15	5800	72150	83850	445.12	22/07/2021	1er	7.52	12.19
TTRC	TRITURAF CI		0	490	NC	NC	0	0.00	490	455	525	1440.00	19/07/2019	2eme	0.00	0.00
UNLC	UNILEVER CI	0	0	4850	NC	NC	0	-0.82	4850	7865	9135	1233.00	09/07/2020	2eme	0.00	0.00
UNXC	UNIWAX CI	808	1683980	2085	2085	2085	-0.24	4.25	2090	3885	4515	18.00	16/08/2021	2eme	0.86	117.28
TOTAL		15644	17510660				NA
PUBLIC SERVICES SECTOR				-6.94%			NA
CIEC	CIE CI	4192	8773320	2095	2100	2095	-0.24	10.55	2100	1840	1695	153.16	25/07/2021	1er	7.96	7.27
ONTBF	ONATEL BF	1238	5221520	4240	4210	4240	0.71	7.48	4210	6245	7255	399.56	01/06/2021	1er	9.49	9.22
SDCC	SODECI	1285	4897025	4050	4100	3750	-7.41	-12.69	4050	39775	46225	337.50	27/08/2021	1er	8.33	8.46
SNTS	SONATEL SN	17445	255870465	14650	14650	14650	0	4.83	14650	20305	23595	1225.00	21/05/2021	1er	8.36	7.28
TOTAL		24160	274762330				NA
FINANCE SECTOR				-16.09%			NA
BICC	BICICI	1275	7901650	6200	6200	6010	-3.06	-18.78	6200	7865	6090	50.00	15/07/2021	1er	0.81	22.12
BOAB	BOA BENIN	3524	21132470	5995	5995	5995	-0.08	13.11	6000	6475	5100	436.00	20/05/2021	1er	7.27	9.14
BOABF	BOA BURKINA FASO	307	1903400	6200	6195	6200	0	0.00	6200	6750	4900	370.00	03/05/2021	1er	5.97	7.75
BOAC	BOA CI	143	772200	5490	5490	5400	-1.64	-7.77	5490	3885	4495	315.00	12/05/2021	1er	5.74	7.72
BOAM	BOA MALI	342	481920	1430	1400	1450	1.4	-2.36	1430	21645	3060			1er	0.00	49.53
BOAN	BOA NIGER	571	3399875	6015	6000	6015	0.25	17.94	6000	3610	4600	429.66	06/05/2021	1er	7.16	10.51
BOAS	BOA SENEGAL	867	2145825	2475	2475	2475	0.2	5.32	2470	2270	2495	161.01	06/07/2021	1er	6.52	7.73
CBIBF	CORIS BANK INTERNATIONAL BF	282	2909300	10800	10250	10800	0	2.86	10800	8605	2495			1er	3.76	10.05
ECOC	ECOBANK CI	7784	33865535	4500	4500	4500	-2.07	-5.96	4595	14800	189			1er	6.40	8.43
ETIT	ECOBANK TRANSNATIONAL INCORPORATED (ETI TG)	248019	5129708	20	20	20	0	11.11	20	23	22	1.21	28/04/2021	1er	0.00	1.87
NSBC	NSIA BANQUE CI	335	1926200	5750	5750	5750	0	-7.03	5750	14800	189			1er	1.35	19.75
ORGT	ORAGROUP TG	982	3829065	3900	3900	3900	-4.06	-6.92	4065	14800	189			1er	1.46	29.89
SAFC	SAFCA CI	132	131340	1160	1160	1075	-7.33	26.47	1160	5740	5740	23.04	29/07/2021	1er	0.00	0.00
SGBC	SGCI	534	6885855	6885855	13105	12995	-0.84	22.65	13105	11990	11840	368.30	30/06/2021	1er	2.81	6.05
SIBC	SIB CI	3339	13466125	3955	3955	4000	1.14	0.38	3955	14800	189			1er	9.10	6.53
TOTAL		268436	105880468				NA
TRANSPORT SECTOR				0.00%			NA
SDSC	BOLLORE TRANSPORT & LOGISTICS CI	45	113000	2500	2400	2500	0	-2.72	2550	3935	3695	100.00	11/08/2021	1er	4.00	10.11
SVOC	MOVIS CI	0	0	2395	NC	NC	0	0.00	2395	2965	2900	270.00	23/07/2021	2eme	0.00	0.00
TOTAL		45	113000				NA
AGRICULTURE SECTOR				-12.42%			NA
PALC	PALM CÔTE D’IVOIRE	1310	11723360	9420	9295	8900	-0.16	34.76	9435	5250	4800	1236.34	31/08/2021	2eme	1.09	41.42
SCRC	SUCRIVOIRE CI	11629	11117870	1015	1075	1015	-7.31	5.73	1095	735	1005			1er	3.70	12.00
SICC	SICOR CI	4	21500	5320	5500	5000	-6.02	-2.34	5320	3655	3530	1919.00	25/09/2020	1er	0.00	3.23
SOGC	SOGB CI	517	2810115	5500	5495	5500	0.09	10.00	5495	3795	2900	541.81	21/07/2021	1er	4.55	15.51
SPHC	SAPH CI	1169	5962125	5150	5145	5150	0.98	-0.87	5100	2740	2800	132.30	24/08/2021	1er	2.59	17.46
TOTAL		14629	31634970				NA
DISTRIBUTION SECTOR				-1.84%			NA
ABJC	SERVAIR ABIDJAN CI	1000	1643825	1650	1640	1650	-5.44	-5.71	1745	1148	1005	164.96	30/09/2020	1er	0.00	0.00
BNBC	BERNABE CI	1088	2615160	2395	2395	2500	4.38	14.94	2395	576	1200	45.00	30/09/2019	1er	0.00	25.18
CFAC	CFAO MOTORS CI	198	232590	1160	1160	1200	0	-2.52	1160	605	430	22.15	15/07/2021	2eme	1.91	55.67
PRSC	TRACTAFRIC MOTORS CI	252	1158140	4600	4600	4600	0	9.52	4600	10	2800	162.90	02/09/2021	1er	3.54	25.28
SHEC	VIVO ENERGY CI	158	147150	925	925	925	-0.54	7.56	930	1172	585	63.90	26/11/2020	2eme	6.80	0.00
TTLC	TOTAL CI	8600	18586860	2160	2200	2160	0	2.86	2160	1961	1475	109.31	27/09/2021	1er	5.06	17.78
TTLS	TOTAL SN	1648	3486710	2095	2100	2095	-0.24	6.08	2100	1634	1445	223.60	30/09/2021	1er	10.65	11.28
TOTAL		12944	27870435				NA
OTHER SECTOR				-7.48%			NA
STAC	SETAO CI	6517	10304135	1805	1670	1670	-7.48	147.26	1805	281	565			2eme	3.66	10.45
TOTAL		6517	10304135				NA
TOTAL - Equities market		342375	468075998				NA

The BRVM_plot(“.company”, “up.col”, “down.col”) function:

This function will get Ticker(s) data and then plot it.

• .company : is the Ticker(s) name(s)
• from : A quoted start date, ie. “2020-01-01” or “2020/01/01”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”.
• to : A quoted end date, ie. “2022-01-31” or “2022/01/31”. The date must be in ymd format “YYYY-MM-DD” or “YYYY/MM/DD”
• up.col : is the up color
• down.col : is down color

chart <- BRVM_plot("BICC") # The default colors for the up and down are green and 
#> [1] "BICC"

#chart

#It is also possible to plot stock data chart for more than one ticker
#Let's plot BICC, ETIT and BOAM stock data

chart1 <- BRVM_plot(c("BICC","ETIT", "BOAM"))
#> [1] "BICC" "ETIT" "BOAM"

# chart1

• BRVM_plot : For one ticker, you can also specify your color like
• BRVM_plot("boas", up.col = "blue", down.col = "pink") for example

The BRVM_company_info(“ticker”) function

It receives the ticker of a company listed on the BRVM stock exchange, Turn to upper case the input by using toupper() and returns informations about the company’s RSI, Beta, Closing price, etc. .

# Get informations such us beta, RSI, Closing, Valorisation, etc. of Bank Of Africa Senegal
inform <- BRVM_company_info("BOAS")
inform

Informations	Values
Volume (titres)	547
Volume (XOF )	1 189 725
Ouverture	2 200
Plus haut	2 200
Plus bas	2 175
Clôture veille	2 265
Beta 1 an	0,07
RSI	36,76
Capital échangé	0,00%
Valorisation	52 200 MXOF

• BRVM_cap() : receives no argument and returns informations about BRVM capitalization

capit_ <- BRVM_cap()
capit_

#> [1] "Make sure you have an active internet connection"

x
Make sure you have an active internet connection

• BRVM_company_rank() : returns companies rank from the BRVM Bourse exchange according to their daily change (variation).

comp.rank <- BRVM_company_rank() #Get companies rank
comp.rank <- comp.rank%>%
    arrange(desc(percent_change)) #Describe in decreasing order

comp.rank

ticker	company_name	percent_change	rank
FTSC	FILTISAC COTE D’IVOIRE	3.60	1
UNXC	UNIWAX COTE D’IVOIRE	2.68	2
SDCC	SODE COTE D’IVOIRE	2.62	3
SGBC	SOCIETE GENERALE COTE D’IVOIRE	1.11	4
SIBC	SOCIETE IVOIRIENNE DE BANQUE COTE D’IVOIRE	1.04	5
SIVC	AIR LIQUIDE COTE D’IVOIRE	0.79	6
BOAM	BANK OF AFRICA MALI	0.42	7
TTLC	TOTAL COTE D’IVOIRE	0.24	8
TTLS	TOTAL SENEGAL	0.20	9
BOAN	BANK OF AFRICA NIGER	0.08	10
BOABF	BANK OF AFRICA BURKINA FASO	0.00	22
BOAC	BANK OF AFRICA COTE D’IVOIRE	0.00	22
CABC	SICABLE COTE D’IVOIRE	0.00	22
ECOC	ECOBANK COTE D’IVOIRE	0.00	22
ETIT	Ecobank Transnational Incorporated TOGO	0.00	22
NEIC	NEI-CEDA COTE D’IVOIRE	0.00	22
NSBC	NSIA BANQUE COTE D’IVOIRE	0.00	22
ONTBF	ONATEL BURKINA FASO	0.00	22
ORGT	ORAGROUP TOGO	0.00	22
PALC	PALM COTE D’IVOIRE	0.00	22
PRSC	TRACTAFRIC MOTORS COTE D’IVOIRE	0.00	22
SAFC	SAFCA COTE D’IVOIRE	0.00	22
SEMC	CROWN SIEM COTE D’IVOIRE	0.00	22
SHEC	VIVO ENERGY COTE D’IVOIRE	0.00	22
SICC	SICOR COTE D’IVOIRE	0.00	22
SLBC	SOLIBRA COTE D’IVOIRE	0.00	22
SMBC	SMB COTE D’IVOIRE	0.00	22
SOGC	SOGB COTE D’IVOIRE	0.00	22
STAC	SETAO COTE D’IVOIRE	0.00	22
STBC	SITAB COTE D’IVOIRE	0.00	22
SVOC	MOVIS COTE D’IVOIRE	0.00	22
TTRC	TRITURAF Ste en Liquid	0.00	22
UNLC	UNILEVER COTE D’IVOIRE	0.00	22
SNTS	SONATEL SENEGAL	-0.03	34
BNBC	BERNABE COTE D’IVOIRE	-0.25	35
ABJC	SERVAIR ABIDJAN COTE D’IVOIRE	-0.39	36
CIEC	CIE COTE D’IVOIRE	-0.47	37
ORAC	ORANGE COTE D’IVOIRE	-0.53	38
CBIBF	CORIS BANK INTERNATIONAL BURKINA FASO	-0.61	39
BOAB	BANK OF AFRICA BENIN	-0.81	40
SDSC	BOLLORE TRANSPORT & LOGISTICS COTE D’IVOIRE	-1.40	41
BICC	BICI COTE D’IVOIRE	-1.95	42
NTLC	NESTLE COTE D’IVOIRE	-2.16	43
BOAS	BANK OF AFRICA SENEGAL	-3.97	44
SPHC	SAPH COTE D’IVOIRE	-4.00	45
SCRC	SUCRIVOIRE COTE D’IVOIRE	-4.23	46
CFAC	CFAO MOTORS COTE D’IVOIRE	-4.29	47

• BRVM_direction(“.up_or_down”) : Takes ‘Up’ or ‘Down’ and returns respectively n results for the top or flop ranking of the BRVM tickers.

• .up_or_down : This is a character string set to “Up” by default It can either be ‘Up’ or ‘Down’.

# Rank in increasing order the price of shares listed on the BRVM according to daily variations.
brvm_down <- BRVM_direction("Down")
brvm_down

Symbole	Nom	Variation (%)
CFAC	CFAO MOTORS COTE D’IVOIRE	-4.29
SCRC	SUCRIVOIRE COTE D’IVOIRE	-4.23
SPHC	SAPH COTE D’IVOIRE	-4.00
BOAS	BANK OF AFRICA SENEGAL	-3.97
NTLC	NESTLE COTE D’IVOIRE	-2.16
BICC	BICI COTE D’IVOIRE	-1.95
SDSC	BOLLORE TRANSPORT & LOGISTICS COTE D’IVOIRE	-1.40
BOAB	BANK OF AFRICA BENIN	-0.81
CBIBF	CORIS BANK INTERNATIONAL BURKINA FASO	-0.61
ORAC	ORANGE COTE D’IVOIRE	-0.53
CIEC	CIE COTE D’IVOIRE	-0.47
ABJC	SERVAIR ABIDJAN COTE D’IVOIRE	-0.39
BNBC	BERNABE COTE D’IVOIRE	-0.25
SNTS	SONATEL SENEGAL	-0.03
BOABF	BANK OF AFRICA BURKINA FASO	0.00
BOAC	BANK OF AFRICA COTE D’IVOIRE	0.00
CABC	SICABLE COTE D’IVOIRE	0.00
ECOC	ECOBANK COTE D’IVOIRE	0.00
ETIT	Ecobank Transnational Incorporated TOGO	0.00
NEIC	NEI-CEDA COTE D’IVOIRE	0.00
NSBC	NSIA BANQUE COTE D’IVOIRE	0.00
ONTBF	ONATEL BURKINA FASO	0.00
ORGT	ORAGROUP TOGO	0.00
PALC	PALM COTE D’IVOIRE	0.00
PRSC	TRACTAFRIC MOTORS COTE D’IVOIRE	0.00
SAFC	SAFCA COTE D’IVOIRE	0.00
SEMC	CROWN SIEM COTE D’IVOIRE	0.00
SHEC	VIVO ENERGY COTE D’IVOIRE	0.00
SICC	SICOR COTE D’IVOIRE	0.00
SLBC	SOLIBRA COTE D’IVOIRE	0.00
SMBC	SMB COTE D’IVOIRE	0.00
SOGC	SOGB COTE D’IVOIRE	0.00
STAC	SETAO COTE D’IVOIRE	0.00
STBC	SITAB COTE D’IVOIRE	0.00
SVOC	MOVIS COTE D’IVOIRE	0.00
TTRC	TRITURAF Ste en Liquid	0.00
UNLC	UNILEVER COTE D’IVOIRE	0.00
BOAN	BANK OF AFRICA NIGER	0.08
TTLS	TOTAL SENEGAL	0.20
TTLC	TOTAL COTE D’IVOIRE	0.24
BOAM	BANK OF AFRICA MALI	0.42
SIVC	AIR LIQUIDE COTE D’IVOIRE	0.79
SIBC	SOCIETE IVOIRIENNE DE BANQUE COTE D’IVOIRE	1.04
SGBC	SOCIETE GENERALE COTE D’IVOIRE	1.11
SDCC	SODE COTE D’IVOIRE	2.62
UNXC	UNIWAX COTE D’IVOIRE	2.68
FTSC	FILTISAC COTE D’IVOIRE	3.60

• BRVM_rank : receives “top” or “flop” and a number ‘n’ and returns table of companies classification

• top_or_flop : Choose between “top” or “flop”

• n : is the number of companies in the classification

#To get top 15
BRVM_rank("top", 15)
#> # A tibble: 15 × 3
#>    Ticker Name                                       `Change (%)`
#>    <chr>  <chr>                                             <dbl>
#>  1 FTSC   FILTISAC COTE D'IVOIRE                             3.6 
#>  2 UNXC   UNIWAX COTE D'IVOIRE                               2.68
#>  3 SDCC   SODE COTE D'IVOIRE                                 2.62
#>  4 SGBC   SOCIETE GENERALE COTE D'IVOIRE                     1.11
#>  5 SIBC   SOCIETE IVOIRIENNE DE BANQUE COTE D'IVOIRE         1.04
#>  6 SIVC   AIR LIQUIDE COTE D'IVOIRE                          0.79
#>  7 BOAM   BANK OF AFRICA MALI                                0.42
#>  8 TTLC   TOTAL COTE D'IVOIRE                                0.24
#>  9 TTLS   TOTAL SENEGAL                                      0.2 
#> 10 BOAN   BANK OF AFRICA NIGER                               0.08
#> 11 BOABF  BANK OF AFRICA BURKINA FASO                        0   
#> 12 BOAC   BANK OF AFRICA COTE D'IVOIRE                       0   
#> 13 CABC   SICABLE COTE D'IVOIRE                              0   
#> 14 ECOC   ECOBANK COTE D'IVOIRE                              0   
#> 15 ETIT   Ecobank Transnational Incorporated TOGO            0

#To get flop 5
BRVM_rank("flop", 5)
#> # A tibble: 5 × 3
#>   Ticker Name                      `Change (%)`
#>   <chr>  <chr>                            <dbl>
#> 1 CFAC   CFAO MOTORS COTE D'IVOIRE        -4.29
#> 2 SCRC   SUCRIVOIRE COTE D'IVOIRE         -4.23
#> 3 SPHC   SAPH COTE D'IVOIRE               -4   
#> 4 BOAS   BANK OF AFRICA SENEGAL           -3.97
#> 5 NTLC   NESTLE COTE D'IVOIRE             -2.16

• company_traded_val(“company”) : receives one company listed on the BRVM stock exchange, Turn to upper case the input by using toupper() and returns informations about the company’s traded value

• company : The name of company listed on the BRVM stock exchange

company_traded_val("ontbf") # Traded value of ONATEL BURKINA FASO
#> [1] "2 280 685"

Authors :

• Koffi Frederic Sessie (koffisessie@gmail.com),

• Abdoul Oudouss Diakité (abdouloudoussdiakite@gmail.com),

• Sanderson Steven(spsanderson@gmail.com)
  

Creator : Koffi Frederic Sessie

cph (Copyright Holder) : Koffi Frederic Sessie

License : MIT 2023, BRVM authors. All rights reserved.